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골관절염 환자에서 관절내 Sodium Hyaluronate(Hyruan®)의 투여가 슬관절통에 미치는 영향
김훈정,임경준,위상우,정종달,유벙식,안태훈,소금영 조선대학교 2000 The Medical Journal of Chosun University Vol.25 No.2
Background : Sodium Hyaluronate has been found to be deficient in the synovial fluid of patients with osteoarthritis. We evaluate the effect of intraarticular Sodium Hyaluronate(Hyruan®) on the knee joint pain in patients with osteoarthritis. Method : Ten patients with osteoarthritis of the knee were participated in this study. Sodium Hyaluronate was injected into knee joints weekly for 5 weeks consecutively. Clinical evaluations were performed using visual analogue scale(VAS) for pain, tenderness and swollen joint counts weekly for the first 5 weeks and at 10 weeks postinjection. Result : VAS, tenderness and swollen joint were all significantly improved from 2 weeks to 10 weeks. There was no complication, except pain on injection site in two patients. Conclusion : Intraarticular injection of Sodium Hyaluronate has been shown to be effective on the treatment of patients with osteoarthritis of the knee.
( Chong Wei Li ),( Rui Qing Song ),( Li Bin Yang ),( Xun Deng ) 한국미생물 · 생명공학회 2015 Journal of microbiology and biotechnology Vol.25 No.8
Trichoderma strain T-33 has been demonstrated to have inhibitory effect on the fungus species Cytospora chrysosperma. Here, an active antifungal compound was obtained from Trichoderma strain T-33 extract via combined separation technologies, including organic solvent extraction, liquid chromatography, and thin-layer chromatography. The purified compound was further characterized by advanced analytical technologies to elucidate its chemical structure. Results indicated that the active antifungal compound in Trichoderma strain T-33 extract is 2,5-cyclohexadiene-1,4-dione-2,6-bis (1,1-dimethylethyl).
Du, Wei,Ma, Xue-Lei,Zhao, Chong,Liu, Tao,Du, Yu-Liang,Kong, Wei-Qi,Wei, Ben-Ling,Yu, Jia-Yun,Li, Yan-Yan,Huang, Jing-Wen,Li, Zi-Kang,Liu, Lei Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.2
Background: MicroRNAs (miRNAs) are an abundant class of endogenous small non-coding RNAs of 20-25 nucleotides in length that function as negative gene regulators. MiRNAs play roles in most biological processes, as well as diverse human diseases including cancer. Recently, many studies investigated the association between SNPs in miR-146a rs2910164, miR-196a2 rs11614913, miR-149 rs229283, miR-499 rs3746444 and colorectal cancer (CRC), which results have been inconclusive. Methodology/Principal Findings: PubMed, EMBASE, CNKI databases were searched with the last search updated on November 5, 2013. For miR-196a2 rs11614913, a significantly decreased risk of CRC development was observed under three genetic models (dominant model: OR = 0.848, 95%CI: 0.735-0.979, P = 0.025; recessive model: OR = 0.838, 95%CI: 0.721-0.974, P = 0.021; homozygous model: OR = 0.754, 95%CI: 0.627-0.907, P = 0.003). In the subgroup analyses, miR-$196a2^*T$ variant was associated with a significantly decreased susceptibility of CRC (allele model: OR = 0.839, 95%CI: 0.749-0.940, P = 0.000; dominant model: OR = 0.770, 95%CI: 0.653-0.980, P = 0.002; recessive model: OR = 0.802, 95%CI: 0.685-0.939, P = 0.006; homozygous model: OR = 0.695, 95%CI: 0.570-0.847, P = 0.000). As for miR-149 rs2292832, the two genetic models (recessive model: OR = 1.199, 95% CI 1.028-1.398, P = 0.021; heterozygous model: OR = 1.226, 95% CI 1.039-1.447, P = 0.013) demonstrated increased susceptibility to CRC. On subgroup analysis, significantly increased susceptibility of CRC was found in the genetic models (recessive model: OR = 1.180, 95% CI 1.008-1.382, P = 0.040; heterozygous model: OR = 1.202, 95% CI 1.013-1.425, P = 0.013) in the Asian group. Conclusions: These findings supported that the miR-196a2 rs11614913 and miR-149 rs2292832 polymorphisms may contribute to susceptibility to CRC.
딥러닝 방식의 웨어러블 센서를 사용한 미국식 수화 인식 시스템
정택위(Teak-Wei Chong),김범준(Beom-Joon Kim) 한국전자통신학회 2020 한국전자통신학회 논문지 Vol.15 No.2
수화는 청각 장애인이 다른 사람들과 의사소통할 수 있도록 설계된 것이다. 그러나 수화는 충분히 대중화되어 있지 않기 때문에 청각 장애인이 수화를 통해서 일반 사람들과 원활하게 의사소통하는 것은 쉽지 않은 문제이다. 이러한 문제점에 착안하여 본 논문에서는 웨어러블 컴퓨팅 및 딥러닝 기반 미국식 수화인식 시스템을 설계하고 구현하였다. 이를 위해서 본 연구에서는 손등과 손가락에 장착되는 총 6개의 IMUs(Inertial Measurement Unit) 센서로 구성된 시스템을 구현하고 이를 이용한 실험을 수행하여 156개 특징이 수집된 데이터 추출을 통해서 총 28개 단어에 대한 미국식 수화 인식 방법을 제안하였다. 특히 LSTM (Long Short-Term Memory) 알고리즘을 사용하여 최대 99.89%의 정확도를 달성할 수 있었고 향후 청각 장애인들의 의사소통에 큰 도움이 될 것으로 예상된다. Sign language was designed for the deaf and dumb people to allow them to communicate with others and connect to the society. However, sign language is uncommon to the rest of the society. The unresolved communication barrier had eventually isolated deaf and dumb people from the society. Hence, this study focused on design and implementation of a wearable sign language interpreter. 6 inertial measurement unit (IMU) were placed on back of hand palm and each fingertips to capture hand and finger movements and orientations. Total of 28 proposed word-based American Sign Language were collected during the experiment, while 156 features were extracted from the collected data for classification. With the used of the long short-term memory (LSTM) algorithm, this system achieved up to 99.89% of accuracy. The high accuracy system performance indicated that this proposed system has a great potential to serve the deaf and dumb communities and resolve the communication gap.
Si Qi Tan(Si Qi Tan),Wen Qi Cher(Wen Qi Cher),Shu-Ling Chong(Shu-Ling Chong),Angelina Su Yin Ang(Angelina Su Yin Ang ),Sashikumar Ganapathy(Sashikumar Ganapathy ),Derrick Wei Shih Chan(Derrick Wei Shi 대한소아신경학회 2022 대한소아신경학회지 Vol.31 No.1
Purpose: Strokes are challenging to diagnose in pediatric emergency departments (EDs) as level of suspicion is low and atypical presentations are common. We analyzed clinical features, epidemiology and factors of delayed identification in arterial ischemic strokes (AIS) and hemorrhagic strokes (HS). Methods: Single-center retrospective cohort study of children aged between 29 days and 18 years old diagnosed with stroke between July 2016 to June 2021. Results: Among 36 children, 11 (30.5%) had AIS, 25 (69.4%) had HS. Median age for AIS was 9 years (interquartile range [IQR], 2 to 9) and HS 9 years (IQR, 1 to 11.5) (P=0.715). Focal neurological deficit was seen in 72.7% of AIS and 20% of HS (P=0.006). Only 18.2% of AIS and 52.0% of HS presented within 6 hours of symptoms. Median time from symptom onset to ED presentation was 24 hours (IQR, 12 to 28) for AIS and 7 hours (IQR, 1.8 to 48) for HS (P=0.595). Most (85.6%) arrived by own transport. Median time from presentation to neuroimaging was 7 hours (IQR, 0.9 to 7) for AIS and 4.8 (IQR, 1.3 to 16.8) hours for HS (P=0.376). Eleven patients, 9/25 (36.0%) HS and 2/11 (18.2%) AIS, did not have stroke as differential diagnosis at ED (P=0.714). Common initial diagnoses were viral illness or headaches. On univariate analysis, age <1 (odds ratio [OR], 17.5; 95% confidence interval [CI], 1.2 to 250.4; P=0.035) and absence of focal neurological deficit (OR, 13.091; 95% CI, 1.5 to 117.9; P=0.022) were significant factors for delayed identification. Conclusion: Index of suspicion for pediatric strokes among caregivers and clinicians should be increased. Public awareness campaigns are recommended.
Wei Huang,Sung-Kwun Oh,Lixin Ding,Hyun-Ki Kim,Su-Chong Joo 대한전기학회 2011 Journal of Electrical Engineering & Technology Vol.6 No.6
We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.
Effects of Ohmic Area Etching on Buffer Breakdown Voltage of AlGaN/GaN HEMT
Chong Wang,Xiao-Xiao Wel,Meng-Di Zhao,Yun-Long He,Xue-Feng Zheng,Wei Mao,Xiao-Hua Ma,Jin-Cheng Zhang,Yue Hao 한국전기전자재료학회 2017 Transactions on Electrical and Electronic Material Vol.18 No.3
This study is on how ohmic area etching affects the buffer breakdown voltage of AlGaN/GaN HEMT. The surfacemorphology of the ohmic metal can be improved by whole etching on the ohmic area. The buffer breakdown voltagesof the samples with whole etching on the ohmic area were improved by the suppression of the metal spikes formedunder the ohmic contact regions during high-temperature annealing. The samples with selective etching on theohmic area were investigated for comparison. In addition, the buffer leakage currents were measured on the differentradii of the wafer, and the uniformity of the buffer leakage currents on the wafer were investigated by PL mappingmeasurement.
Identification of Fuzzy Inference System Based on Information Granulation
( Wei Huang ),( Lixin Ding ),( Sung-kwun Oh ),( Chang-won Jeong ),( Su-chong Joo ) 한국인터넷정보학회 2010 KSII Transactions on Internet and Information Syst Vol.4 No.4
In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with “conventional” evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some “conventional” fuzzy models already encountered in the literature.